a Lectin Ligands: New Insights into H.-C. Siebert Their ... · mechanics, molecular dynamics and...

© 1998 S. KargerAG, Basel0001–5180/98/1614–0091$15.00/0

Fax¤+¤41 61 306 12 34E-Mail [email protected] Accessible online at:www.karger.com http://BioMedNet.com/karger

C.-W. von der Lieth a

H.-C. Siebert b

T. Kozár c, d

M. Burchert b

M. Frank a

M. Gilleron e

H. Kaltner b

G. Kayser a

E. Tajkhorshid a

N.V. Bovin f

J.F.G. Vliegenthart g

H.-J. Gabius b

a Deutsches Krebsforschungszentrum,Zentrale Spektroskopie, Heidelberg, and

b Institut für Physiologische Chemie,Tierärztliche Fakultät,Ludwig-Maximilians-Universität,München, Germany

c Glyco-Design, Toronto, Canada;d Department of Biophysics, Institute of

Experimental Physics, Slovak Academy ofSciences, Kosice, Slovakia;

e Institut de Pharmacologie et de BiologieStructurale du CNRS, Toulouse, France;

f Shemyakin Institute of BioorganicChemistry, Russian Academy of Sciences,Moscow, Russia;

g Bijvoet Center for Biomolecular Research,Department of Bio-Organic Chemistry,Utrecht University, Utrecht,The Netherlands

Acta Anat 1998;161:91–109

Dr. C.-W. von der LiethDeutsches Krebsforschungszentrum, Zentrale SpektroskopieIm Neuenheimer Feld 280, D–69120 Heidelberg (Germany)Tel. +49 6221 424541, Fax +49 6221 4554E-Mail [email protected]

ooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooo

Key WordsLectin · NMR spectroscopy · Crystallography · Molecular modeling · Drug design

AbstractThe mysteries of the functions of complex glycoconjugates have enthralled sci-entists over decades. Theoretical considerations have ascribed an enormouscapacity to store information to oligosaccharides. In the interplay with lectinssugar-code words of complex carbohydrate structures can be deciphered. Tocapitalize on knowledge about this type of molecular recognition for rationalmarker/drug design, the intimate details of the recognition process must bedelineated. To this aim the required approach is garnered from several fields,profiting from advances primarily in X-ray crystallography, nuclear magneticresonance spectroscopy and computational calculations encompassing molecularmechanics, molecular dynamics and homology modeling. Collectively consid-ered, the results force us to jettison the preconception of a rigid ligand structure.On the contrary, a carbohydrate ligand may move rather freely between two oreven more low-energy positions, affording the basis for conformer selection bya lectin. By an exemplary illustration of the interdisciplinary approach includ-ing up-to-date refinements in carbohydrate modeling it is underscored why thiscombination is considered to show promise of fostering innovative strategies inrational marker/drug design.oooooooooooooooooooo

Introduction

The astounding complexity of glycosylation raises theimpression at first sight that revealing the enigmas of com-plex carbohydrate structures and functions can be the sci-entist’s version of ‘Mission: Impossible’. Definitely, suchconcern can be allayed immediately and convincingly.

Lectin Ligands: New Insights intoTheir Conformations andTheir Dynamic Behavior and theDiscovery of Conformer Selectionby Lectins

Abbreviations used in this paper:CIDNP¤=¤Chemically induced dynamic nuclear polarization; NMR¤=¤nuclear magneticresonance; NOE¤=¤nuclear Overhauser effect; trNOE¤=¤transferred nuclear Overhausereffect; 2D/3D¤=¤two-/three-dimensional.

Dedicated to Prof. F. Cramer on the occasion of his 75th birthday.

Dow

nloa

ded

by:

UB

der

LM

U M

ünch

en

129.

187.

254.

47 -

7/2

9/20

13 1

2:50

:48

PM

Building a solid foundation, the efforts in this area overseveral decades have primarily focused on glycoconjugatepurification and cataloguing [Montreuil, 1995; Sharon,1998]. Without precise knowledge about the rules of bio-chemical glycosylation it would be a rather audacious en-deavor to deal with the issue of carbohydrates as moleculesin search of a function [Cook, 1986, 1995]. The recent de-velopments make it reasonable to endorse the notion thatwe have entered a stage in which we deliberately work onhypotheses for the multipurpose oligosaccharides. Indeed,elegant and efficient strategies have been established forglycoconjugate analysis [Hounsell, 1997; Geyer and Geyer,1998]. The intricacies of enzymatic protein and lipid glyco-sylation are being steadily unraveled [Brockhausen andSchachter, 1997; Kopitz, 1997; Pavelka, 1997; Varki, 1998]and the ideas about the actual properties imparted by thepresence of oligosaccharides on the carrier become moreand more refined [Gahmberg and Tolvanen, 1996; Hooperet al., 1997; Kopitz, 1997; Kresse, 1997; Sharon and Lis,1997]. Thus, we are witnessing the shaping of the careerof this structural part of cellular glycoconjugates from anassumed functionally inert compound, recently ironicallyreferred to as a ‘second-class citizen in biomedicine’ [vonder Lieth et al., 1997a], to a crucial player in protein andcell functions. As attested by the potency of glycan chainson proteins to elicit antibody production, what is still con-sidered as a troublesome origin of epitope cross-reactivityby glycoproteins [Feizi and Childs, 1987], carrier-boundoligosaccharides can be well accessible for appropriate re-ceptors such as an immunoglobulin. The spatial accessibil-ity is the basis to allow monitoring of occurrence of distinctcarbohydrate epitopes by antibodies or lectins. The latterclass of sugar receptors harbors neither antibodies nor en-zymes with activity in carbohydrate remodeling or metabo-lism and has shared the scientific fate of complex carbohy-drates also over decades as proteins in search of a function[Kocourek, 1986; Sharon and Lis, 1987; Gabius, 1994].

Commonly, plant and invertebrate lectins are employedas tools for glycoconjugate analysis and localization [Lotanand Nicolson, 1979; Spicer and Schulte, 1992; Gabius andGabius, 1993; Danguy et al., 1994, 1998; Danguy, 1995;Cummings, 1997; Rhodes and Milton, 1998]. Localizationin tissue sections, e.g. to detect developmental or malig-nancy-associated changes in glycoconjugate display, simi-larly takes advantage of this panel of probes [Mann, 1988;Bourillon and Aubery, 1989; Hakomori, 1989, 1998; Varkiand Marth, 1995; Kannan and Nair, 1997; Brinck et al.,1998; Brockhausen et al., 1998; Mann and Waterman,1998; Zschäbitz, 1998]. Its proven versatility not onlyfuels work on elucidation of the functions of these proteins

in plants and invertebrates such as the horseshoe crab[Etzler, 1985; Vasta, 1992; Peumans and van Damme,1995; Gabius, 1997a; Rüdiger, 1997, 1998]. Moreover, thedescription of apparently strictly and exquisitely regulatedoccurrence of distinct binding sites for these body-foreignproteins poignantly points to the possibility that their ex-pression is not just guided by chance. Compelling evi-dence documents that functional equivalents of these lectinsused as laboratory tools are expressed in animals [Ashwelland Harford, 1982; Barondes, 1984; Gabius, 1987, 1991,1997a, b; Sharon and Lis, 1989; Zanetta, 1997, 1998; Kalt-ner and Stierstorfer, 1998]. Owing to mastering the tasksto prepare synthetic oligosaccharides and to conjugate themto histochemically inert carrier polymers the produced neo-glycoconjugates have already become an approved part ininvestigations to track down animal lectins [Stowell andLee, 1980; Gabius and Bardosi, 1991; Gabius et al., 1993;Lee and Lee, 1994; Bovin and Gabius, 1995; André et al.,1997; Schmidt, 1997]. Their expression is decisive for thecredibility of the concept of a productive protein-carbo-hydrate interaction, the lectins assuming the assignment toread the information of the sugar code. Similar to oligo-and polymers of nucleotides and amino acids which pro-ductively interact with proteins it is therefore justified to as-cribe information-storing potential also to oligosaccharides.This aspect reveals the diversity of glycan structures in adifferent light, changing the assessment of their complexityfrom predominantly phenomenological cataloguing to list-ing of determinants with a potential for recognitive inter-

92 Acta Anat 1998;161:91–109 von der Lieth/Siebert/Kozár/Burchert/Frank/Gilleron/Kaltner/Kayser/Tajkhorshid/Bovin/Vliegenthart/Gabius

Fig. 1. Schematic representation of the geometric arrangement ofmonomers in oligo- and polymeric biomolecules establishing thecommonly linear structures of nucleic acids and proteins (a). In con-trast to these two types of biomolecules formation of the glycosidicbond in oligosaccharides which can involve different hydroxyl groups(see fig.¤2) affords the capacity to generate branched structures (b).

a

b

Dow

nloa

ded

by:

UB

der

LM

U M

ünch

en

129.

187.

254.

47 -

7/2

9/20

13 1

2:50

:48

PM

play. A hallmark of such sequences is their often occurringbranching, which is only rarely encountered in proteins andnucleic acids (fig.¤1). From the point-of-view of storage ofinformation, this structural feature has enormous conse-quences [Laine, 1997].

The Structural Basis of the Sugar Code

In contrast to peptide and 5′,3′-phosphodiester bonds thechemical formation of the glycosidic linkage between twomonosaccharides can yield several structurally different

disaccharides. Due to the eminent importance of this fea-ture it is instructive to recall some basic biochemistry. Vi-sualizing the most common hexose D-glucose in its stableform as intramolecular hemiacetal, the presentation of fivehydroxyl groups explains the potential for structural vari-ability of oligomers and for branch formation (fig.¤2, upperpart). When a monosaccharide engages its anomeric hy-droxyl group (α- or β-form) in a glycosidic linkage, the co-valent connection to the second hexopyranose ring can the-oretically be made via the indicated five positions (fig.¤2,bottom). Further elongation of the chain from the non-reducing section can theoretically use any combination of

93Conformational Behavior of Lectin Ligands Acta Anat 1998;161:91–109

Fig. 2. Diagram of the various depictions of the structure of a monosaccharide (α-D-glucose; top) as intramolecu-lar hemiacetal without explicit indication of the relative positions of the atomic groups in space (left) and in the Haworthprojection (center). This method defines these positions relative to the plane of the ring which is perpendicular to theplane of the paper with the heavy line on the ring closest to the reader. The most refined form of structural representa-tion of the preferred conformation is the chair with the equatorial and axial substituents (right). Diagram of the struc-tural basis for the generation of linear and branched oligomers (bottom), shown in figure 1. A glycosidic linkage in-volving the β-anomeric hydroxyl group of the left monosaccharide (D-galactose) can theoretically be formed with anyhydroxyl group of the acceptor (D-glucose), yielding β1-1, β1-2, β1-3, β1-4 or β1-6 connections (arrows). A disaccha-ride with a β1,2 linkage between two D-galactose units is exemplarily shown in figure 3.

Dow

nloa

ded

by:

UB

der

LM

U M

ünch

en

129.

187.

254.

47 -

7/2

9/20

13 1

2:50

:48

PM

available hydroxyl groups. Consequently, a chain struc-ture can readily obtain branches, schematically drawn in fig-ure 1b, by further involvement of the free and spatiallyaccessible groups. The factors of variable anomeric config-uration and linkage position as well as the introduction ofbranching points at each sugar unit contribute markedly tolet the numbers of the theoretically possible repertoire of iso-meric structures skyrocket. Respective calculations demon-strate that carbohydrates surpass by far the coding potentialof amino acids [Laine, 1997]. In detail, 6.4¤×¤107 hexapep-tides can be generated from twenty amino acids. Applyingpermutational calculations to a set of only six D-hexoses,1.05¤¥1012 different linear or branched hexasaccharides canbe imagined. Allowing the size of the monomer vocabu-lary to reach twenty letters to equal amino acids, a total of1.44¤×¤1015 isomers will be reached [Laine, 1997]. However,it is pertinent to point out that the enzymatic machinery ofcellular glycosylation sets limits to the actual productionof any theoretically devisable permutation restricting thesize of the isomer pool [Brockhausen and Schachter, 1997].Enzymatic reactions, however, can also serve to diversifyestablished oligosaccharides which thereby acquire nonran-dom substitutions. As a balancing factor to the noted re-striction and therefore as source for new variability, theoccurrence of uncommon saccharide derivatives by site-specific modifications, e.g. sulfation, O-acetylation or phos-

phorylation, has already proven functionally relevant asdocking points for lectins [Varki, 1996; Hooper et al., 1997;Sharon and Lis, 1997]. In summary, it is beyond doubt thatthe hardware of the sugar code, i.e. the monosaccharide let-ters of the third alphabet of life, establishes the prerequi-sites for the ‘most complex known chemical code in a shortsequence among all biological oligomers’ [Laine, 1997].

When a protein such as a lectin recognizes specific codeelements, it does no longer suffice to deliberate only on theprimary structure of the ligand. After the elaboration of an-alytical methods to reliably unravel the sequence the nextchallenge is posed by the necessity for the description ofthe conformation and the structural flexibility of oligosac-charides in order to comprehend their ligand properties.When the structure of two linked hexopyranose rings iscarefully inspected, this problem turns out to be less com-plicated than initially thought. The main source of spatialalterations for saccharides resides in the bonds of the gly-cosidic linkage due to the rather rigid ring structure withtheir pronounced energetic preference for the chair confor-mation. As shown in figure 3, both dihedral torsion anglesφand ψ of these two exocyclic bonds can be independentlyvaried, thereby altering the relative positions of the tworings. By letting the thumbs of each hand touch in the ap-propriate angle and then by moving each hand indepen-dently without losing the contact of the thumbs, the reader


Fig. 3. Structural representation of the disaccharide gal-β1,2-gal with emphasis on depiction of the origin of con-formational flexibility by independent rotations about the dihedral angles φand ψ of the glycosidic bond.

Dow

nloa

ded

by:

UB

der

LM

U M

ünch

en

129.

187.

254.

47 -

7/2

9/20

13 1

2:50

:48

PM

can easily visualize the principle of φ, ψ-flexibility withhis hands. The questions immediately arise of which anglepositions will be energetically preferred for individualoligomers, to what extent conformational flexibility willexist and whether binding of the ligand to a receptor maydistort predominant angle positions. To assail the solutionof these problems, whose acquisition will have far-reachingconsequences for drug design [Gabius, 1998], a combinedapplication of computer modeling and nuclear magneticresonance (NMR) spectroscopy is essential.

Oligosaccharide Flexibility: No Longer aHidden Aspect of the Ligand’s Personality

The two torsion angles φ and ψ define the conforma-tional space for any disaccharide. Drawing the analogy totopographical maps, the area of a diagrammatic φ, ψ-repre-sentation receives its third dimension not by altitude, but bythe energy content of each conformation, defined by a cer-tain φ, ψ-combination. The total potential energy for any φ,ψ-set can be calculated, if the individual energetic contri-butions are adequately taken into consideration. Factors tobe reckoned with include e.g. bond deformations, valenceangle distortions and nonbonded interactions. They arecarefully compiled and a set of equations is developedwhich establish a force field, as reviewed recently [Pérez etal., 1994; Woods et al., 1995; Woods, 1996; Imberty, 1997;Rasmussen, 1997; von der Lieth et al., 1997b]. To limit thenumber of the otherwise prohibitively long series of calcu-lations, a grid is established by drawing lines with a regulardistance, e.g. 20°, into the φ, ψ-area marking selected tor-sion angle combinations (fig.¤4a, b, 5a–c). At this stage,inspection of the other rotatable bonds in the molecule, e.g.of hydroxyl groups, comes into play. The energetic descrip-tion of low-energy configurations becomes more and morerefined. To obtain the desired topographical illustration foreach grid intersection, all rotatable bonds in the moleculebesides the fixed φ, ψ-combination will have to be exam-ined. By randomly generating an ensemble of internal con-formers, which usually is in the order of magnitude of thou-sands, and evaluating the relative energy content in eachcase, this random walk of rotatable groups provides datamaterial for further processing. The nondirected movementof the pendant groups has prompted to refer to this methodas random walk molecular mechanics [Kozár et al., 1990].In the next step, an energy cutoff limit is defined to setbounds to the number of calculations for optimization ofthe so far randomly produced angle combinations at eachgrid point. In other words, one is not interested to expend

time and efforts on high-energy conformations, when theaim is to infer the topology of low-energy constellations. Atthe end of these calculations the number of fixed coordi-nates of the molecules’ geometry is cut down to the bondsof the ring and the φ, ψ-torsion angles of the grid point.The next step in the procedure can thus be readily pre-dicted. Following the analysis of the rotatable linkages ofOH and CH2OH groups (see fig.¤2) optimization of the mol-ecules’ geometry moves to the other internal bonds exceptfor the grid-defined two angle positions. The final results ofthese calculations are the three- (3D) or two-dimensional(2D) maps, referred to as adiabatic or relaxed conforma-tional energy maps (fig.¤4a, b, 5a–c). These maps reveal thatthe conformational space of a disaccharide can be visual-ized as a hilly landscape. Remarkably, not just one, but sev-eral low energy positions can be inferred for the two in-spected digalactosides. Similarly intriguing is the answer tothe question of whether the position of the glycosidic link-age will alter the energy profile. When the maps for twodigalactosides which differ only in their linkage points (i.e.1,2 vs. 1,3) are compared (ε¤=¤1.5, fig.¤4a, b, 5a), it is evi-dent that the shape of the central low-energy valley is dif-ferent. Disparities in the presentation of functional groupsdue to the change in linkage point and/or in the conforma-tional behavior may explain the more than 2-fold differencein inhibitory capacity of the two digalactosides in a bindingassay for a plant lectin [Lee et al., 1992, 1994; Galaninaet al., 1997]. Overall, these relaxed maps underscore theimportance of exploring the conformational space of anoligosaccharide. The term ‘relaxed’ indicates that no artifi-cial strain is imposed in the molecules’ geometry to simu-late the conformational behavior as realistically as possible.It also reminds one of the initial grid constraint which re-mains to be considered.

At this stage, the ring geometry and the rotatable pen-dant groups have been optimized. To prevent being deludedinto the notion that the description of the correlation be-tween conformation and energy content is complete, thefinal step to alleviate the inherent φ, ψ-constraint must notbe neglected. The necessity for lifting the grid-imposed re-strictions becomes evident, when a worst-case scenario isdevised. If an actual energy minimum conformation is notlocated in the vicinity of a grid point, it can be missed,reducing the value of the calculations. To completely sim-ulate the conformational behavior the final optimizationshould allow φ, ψ-angles to leave the fixed grid points.Low-energy conformations will now appear as clusters(shown in fig.¤4, 5) after energy minimization without con-straint [Kozár and von der Lieth, 1997]. Again alluding tothe analogy of a hilly countryside, these clusters can be


Dow

nloa

ded

by:

UB

der

LM

U M

ünch

en

129.

187.

254.

47 -

7/2

9/20

13 1

2:50

:48

PM

considered as low-altitude positions. When balls are al-lowed to freely take their path from any starting point in thelandscape, they will end up in a distinct set of positions (theequivalent of conformational clusters) after taking a suit-able downhill route, as seen in figures 4a, 5d. Energy bar-riers between local minima can preclude the final move-ment of the balls into a – if present – global ‘low-altitudeposition’. The decision on the starting point governs the ar-

rival at the final destination. Therefore, several clusters areapparent in the 3D/2D representations (fig.¤4a, 5d). Theiroccurrence prompts the pertinent question of what will hap-pen when thermal energy in the biologically acceptablerange is available to the molecules. Inherently, the molecu-lar mechanics calculations will not answer the question ofwhether and how often an energy barrier will be crosseddue to the permanent internal movements of the molecule at


Fig. 4. Energy profile of the conformational space of the disaccharide gal-β1,2-gal, shown in figure 3, based oncomputer-assisted calculations. Comparable to topographic maps the energy levels of each φ, ψ-angle combination ofa systematic grid search can be shown in 3D (a) or 2D (b) representations (contour lines denote energy levels inkcal/mol). Low-energy positions can independently be calculated by the conformational clustering approach, indicatedby red crosses in the 3D map (a).

a

b

Dow

nloa

ded

by:

UB

der

LM

U M

ünch

en

129.

187.

254.

47 -

7/2

9/20

13 1

2:50

:48

PM

37¤°C. Consideration of the factor ‘time’, establishing tra-jectories of angle fluctuations, leads to molecular dynamicscalculations with the aim to describe the traffic of mole-cules between local energy valleys separated by barriers[von der Lieth et al., 1997b].

Molecular dynamics calculations describe the motionalbehavior of a system of atoms at a certain temperatureusing differential equations of motion in the context of aforce field. The alterations of location by molecular mo-tions, so-called trajectories, can be visualized as a series of


Fig. 5. Energy profile representation of the results of random walk molecular mechanics calculations (energy lev-els from 0 to 10 kcal/mol) and of the conformational clustering approach (low-energy positions marked by crosses) forthe disaccharide gal-β1,3-gal with consideration of different dielectric constants [ε¤=¤1.5 (a), b: ε¤=¤4 (b), c: ε¤=¤80 (c)]and illustration of the results of the conformational clustering approach (low-energy positions marked by crosses)revealing the initial and final positions for this disaccharide at ε¤=¤80 (d).

a

c d

b

Dow

nloa

ded

by:

UB

der

LM

U M

ünch

en

129.

187.

254.

47 -

7/2

9/20

13 1

2:50

:48

PM

snapshots of a molecule after distinct periods of time. Theselection of the length of this interval is determined by thevelocity of the fastest vibrations within the molecule. Toclosely follow stepwise alterations of any aspect of confor-mation, the ‘snapshot’ should be recorded before e.g. oneC-H stretch vibration is completed and the next vibration isalready under way. Consequently, periods of 1 fs (10–15 s)are chosen to be able to establish trajectories of φ, ψ-alter-ations. They are sufficient to account for the behavior of themolecule during the period of individual stretch vibrationswhich are measured to last approximately 10 fs. Examples

of trajectories for the two torsion angles of a disaccharideare shown in figure 6. They reveal the population of the twolocal energy minimum conformations in the central low-energy valley owing to frequent fluctuations between thetwo ψ-positions which are marked by crosses (fig.¤4a) or thetopographical designations (fig.¤4b). Positions of 180°/–180°for the ψ-angle are not populated. They are not even stable,when chosen as starting point for the molecular dynamicsrun. Remarkably, this calculation includes the presence ofsolvent molecules, which generally damp the frequencyof oscillations and transitions [Kozár and von der Lieth,


Fig. 6. Illustration of the disaccharidegal-β1,2-gal which is surrounded by watermolecules (upper part). When the dynamicbehavior of the disaccharide concerning theφ, ψ -angle position is calculated for a periodof 1,000 ps with explicit consideration ofpresence of water molecules, the disaccha-ride preferentially exhibits angle positions inthe central low-energy valley (bottom).

Dow

nloa

ded

by:

UB

der

LM

U M

ünch

en

129.

187.

254.

47 -

7/2

9/20

13 1

2:50

:48

PM

1997]. In view of biological systems with water, their con-sideration is essential, although the number of equations ofmotions automatically increases. The square of the numberof atoms in the system is relevant to estimate the durationof the calculations. If the size of the calculations exceedsa reasonable computational time to complete the run, theeffect of solvent molecules is approximated by choosing acertain value for the dielectric constant.

Although this procedure certainly is a simplification ofthe complex system established by an oligosaccharide insolution, these approximations are generally approved of,until the problem of the enormous size of calculation stepsto be preferably carried out in a few hours is solved. Sincethis parameter change also is of relevance for molecularmechanics calculations, its impact warrants attention in thisfield. As evident from figure 5a–c, molecular mechanicscalculations are affected quantitatively, but not qualitativelyby the deliberate change of ε-values from 1.5 to 4.0 or 80,underscoring the practicability of this approach. Its currentnecessity is emphasized by the following appendix.

Practically, simulation periods cover the range of 1 ns.To give an idea on the required calculation time for sucha run on a unix workstation for a disaccharide, it is men-tioned that in the case of maltose and vacuum as simulatedenvironment 3 h can be expected to complete the process-ing. When the disaccharide is embedded in a solvent boxwith 1,443 water molecules, the same workstation has to bebusy full-time for 635 h [von der Lieth et al., 1997b].

As illustrated in figures 4 and 6, the combination ofmolecular mechanics and molecular dynamics simulationsprovides insights into the positions of low-energy confor-mations in the φ, ψ-map and the frequency of transitionsbetween such conformations. Evidently, oligosaccharidescannot not superficially be referred to as rigid molecules.In contrast, the concept of the possibility for an ensembleof energetically favorable conformers as ligands is increas-ingly appreciated [Hardy, 1997; von der Lieth et al., 1997b;Gabius, 1998]. This knowledge has far-reaching conse-quences for the understanding of protein-carbohydrate in-teraction. Detailed calculations for any sugar compound areindispensable, because a low-energy conformer can in prin-ciple be the object of selection by a receptor. The factsthat various conformational families can be discerned welland that their relative share on the total population can beconstant or can vary with sequence alterations are e.g. em-phasized for blood group H trisaccharides. Whereas the tri-saccharides of H type 1, type 2 and type 6 blood groupepitopes preferentially take up one conformation with onlya share of 3.5–5% of the total population residing in theminor conformation, H type 3 and type 4 trisaccharides dis-

play different features [Imberty et al., 1995]. Their popula-tions are rather equally distributed between two conforma-tional families. Especially when low-energy conformationsare positioned in different sections of a rather extendedlow-energy-level valley, frequent transitions between twopositions separated only by a minor barrier can occur, asalso recently shown for disaccharide ligands of galactoside-binding lectins [Gilleron et al., 1998]. This situation callsfor answering the question about the spatial parameters of aflexible ligand after complex formation with a receptor. Be-fore this issue will be addressed, it must not be overlookedthat our reasoning on flexibility up to this point exclusivelyrests on computer-assisted calculations. Their results needto be ascertained by experimental input.

An indication for the inherent flexibility is given by theoften noted difficulty to crystallize complex carbohydrates.Even if successful, crystallography cannot reflect the dy-namic behavior of molecules in solution. Therefore, spec-troscopic techniques which afford the capacity to monitormolecules in solution are essential, as already emphasizedby Geyer and Geyer [1998] in this issue with respect tothe structural analysis of the glycan part of glycoconju-gates. In NMR spectroscopy through-space dipolar inter-actions between protons which act as transmitter-receiverpair, if placed in spatial vicinity (the distance is generallysmaller than 3.5 Å for oligosaccharides) for a finite timeperiod, are a valuable source of information [Carver, 1993;Homans, 1995; Siebert et al., 1997b]. These contacts can beintra- and interresidual. To gather information on φ, ψ-com-binations, only interresidual contacts are useful, whichqualify to draw conclusions on the φ, ψ-features, as indi-cated in figure 7a, b. If a molecule is completely rigid, themeasurement of these nuclear Overhauser effects (NOE)allows to unequivocally translate the signal intensities intointernuclear distances, employing the spectroscopic signalas molecular ruler. For a rather rigid molecule no furthercomplications affect the interpretation. However, the inher-ent flexibility with rapid fluctuations hampers such straight-forward derivation of conclusions in most cases. The rep-resentation of the NMR-derived information as a single(virtual) conformation can then be misleading. It is essen-tial to keep in mind that individual conformers will con-tribute to the overall signal, because the comparatively longtime frame of the measurement cannot distinguish betweenthe frequently and rapidly changing positions. The lack ofability to carry out snapshots in the ps range with the NMRspectrometer causes inevitable time- and ensemble-aver-aging over all contributing conformers [Jardetzky, 1980;Carver, 1991; Pearlman, 1994; Siebert et al., 1997b]. Sincethe number of interresidual contacts in oligosaccharides is


Dow

nloa

ded

by:

UB

der

LM

U M

ünch

en

129.

187.

254.

47 -

7/2

9/20

13 1

2:50

:48

PM

generally small, the availability of only one or few distanceconstraint(s) and the problem of averaging preclude a pre-cise depiction of an actual conformation. However, at leastthe problem of averaging is not insurmountable.

To generate an NOE, two protons come into a dipolarcontact over a fixed distance or over two or more individualdistances which are averaged during the measurement. Tak-ing flexibility into account, the probably averaged signalcan originate from e.g. two distances. This assumption isthe basis of the distance-mapping approach [Poppe et al.,1990; Siebert et al., 1997b; von der Lieth et al., 1997b].The actual presence of an interresidual dipolar contact isattributed to two true distances, which yield the measurabledistance upon averaging. The lower limit for the distanceof 2.0 Å is given by the van der Waals radii. As alreadyindicated for carbohydrates in the preceding paragraph, anupper limit will not generally exceed 3.5 Å, because the

strength of the through-space magnetization transfer fadesaway with an r –6 dependence on the distance betweensender and receiver protons. Upper and lower limits encir-cle a section of the φ, ψ-space by contour lines. This set ofcontour lines defines an ensemble of φ, ψ-combinationswhich are consistent with the distance constraint(s) derivedfrom the NMR experiment. The principal idea is drawn infigures 8a and 9a. Weighting of this total population of φ,ψ-combinations can be performed by combining the illus-trations of the mapping approach with the results of molec-ular mechanics calculations. If a second distance constraintis available, the size of the population with compatible φ,ψ-combinations in the area of overlap is drastically re-duced, as easily apparent in figures 8a and 9a. Again, ac-counting of energy levels in this marked area is conduciveto infer conformational parameters of a disaccharide. Thus,NMR-derived distance constraints are helpful to deduce


Fig. 7. Representation of a trNOE spectrum of the complex between the galactoside-specific mistletoe lectin andthe disaccharide gal-β1,4-glcNAc irradiated with the resonance frequency of the anomeric proton of the galactose moi-ety (Gal H1). It shows evidence for a through-space magnetization transfer to an intraresidual proton (Gal H3) and toan interresidual proton (GlcNAc H4). These signal intensities allow to calculate the average distances (in Å) to theanomeric proton, given in b. Any interresidual contact is relevant to delimit the accessible conformational space definedby φ, ψ-combinations.

a b

Dow

nloa

ded

by:

UB

der

LM

U M

ünch

en

129.

187.

254.

47 -

7/2

9/20

13 1

2:50

:48

PM

whether conformational energy valleys can be populated insolution. If they do not fit into the area delimited by a set ofcontour lines in the distance-mapping approach, the proba-bility for the occurrence of the corresponding φ, ψ-combi-nations is negligible. These constraints can also be assessedexperimentally for ligands associating to a receptor andrapidly exchanging between solution and the binding site.The monitoring of transferred NOE (trNOE) in receptor/ligand mixtures at subsaturational receptor concentrationsprovides a means to characterize spatial features of thebound ligand [Lian et al., 1994; Ni, 1994].

The Ligand’s Topology in Complex with theLectin

A complete elucidation of the ligand’s conformation inthe binding pocket by NMR spectroscopy would require tocollect the entire set of resonances from the complexedmolecules in technically demanding multidimensional NMRtechniques [Hull, 1994]. The sheer quantity of signalswhich must be ascribed to individual protons limits thescope of this sophisticated method to rather small proteins.It is not surprising under these circumstances that the small-est known lectin, i.e. hevein with its 43 amino acids, has sofar been the prime target for this approach [Asensio et al.,1995]. Although astounding progress is currently made inthis area and isotope-enriched receptors and ligands cansimplify the task, the magnetization transfer between ligandprotons is still sure to be a major source of topologicalinformation. trNOEs are visible as sharp negative signals inthe spectrum (fig.¤7). As already explained in the preced-ing paragraph, the intensities of intraresidual signals cali-brate the distance scale and facilitate to translate peak sizesinto average distances for any interresidual contact (fig.¤7).However, one factor must not be disregarded to safelyreach a flawless interpretation. When the ligand associateswith its receptor, protons of the ligand will come into spa-tial vicinity of protons from amino acids establishing thebinding site. Since the through-space magnetization trans-fer will not distinguish between protons of the ligand orreceptor, protein protons can indirectly be involved in thisprocess as mediators to let ligand protons communicate[Arepalli et al., 1995; Peters and Pinto, 1996; Siebert et al.,1997b]. This process is graphically denoted as spin diffu-sion. Adequate technical procedures have already been sug-gested to eliminate the possibility to be led astray, e.g. shortmixing times at low ligand concentrations or monitoring inthe rotating frame under spin-locking conditions. The pro-tocols ensure the validity of trNOE-derived conclusions.

The technique to measure magnetization transfer of aligand’s proton in the presence of the receptor thus invitesthe exploration of the question of whether individual con-formers of an oligosaccharide can be selected by distinctreceptors. Recalling the presentation of the dynamic prop-erties of the disaccharide gal-β1, 2-gal in figure 6, it hasbeen tempting to analyze lectin/ligand complexes to revealwhether conformer selection is actually operative for dif-ferent types of lectin. In that case, cell biologists and histo-chemists can rightfully glean the take-home message fromsuch experiments that besides the sequence the conforma-tion of the lectin ligand must be clarified to comprehend thedetails of the recognitive interplay.

Independent origins of binding sites can make it likelythat their architectures will differ. Since the disaccharideunder scrutiny is known to bind to plant and animal lectins[Lee et al., 1992, 1994; Siebert et al., 1996], monitoring oftrNOE for the galactoside-binding lectins from a plant (Vis-cum album L.) and an animal (chicken liver galectin) wasinstrumental to answer this question [Siebert et al., 1996;Gilleron et al., 1998]. As shown in figures 8 and 9, the con-cept of differential conformer selection by the two lectinswith the same nominal specificity to D-galactose was veri-fied. In complete agreement with the results of the com-puter calculations, experimental evidence for the presenceof the two predicted conformations for the free ligand insolution was provided by NMR spectroscopy (fig.¤10). Twoof the three interresidual contacts which are visible for thefree ligand are characteristic for the two different com-plexes (see schematic depiction of the two contacts in theright parts of fig.¤8 and 9, respectively, relative to fig.¤10).Notably, no marked alteration in the conformation of theligand appeared to take place upon binding of the chosenconformer. This conclusion is reinforced by a recent docu-mentation that the three selectins (E- and P-selectin vs. L-selectin) also use conformer selection in ligand recognition[Poppe et al., 1997]. Thus, a snugly and thermodynamicallyfavorable fit of substantial portions of the ligand into abinding site is feasible from various positions of a low-energy valley. With curiosity this result is set into relationto the information from crystallography.

Unfortunately, these proteins have so far not been ana-lyzed as complexes in crystals, which only permits a gen-eral comparison including mentioning of two potentialshortcomings of this technique. Although the aim of crys-tallization often calls for nonphysiological conditions tofavor crystal initiation and growth, and although the pack-aging in the rigid crystal structure may distort sensitiveconformational features of the solution structure, it is reas-suring to note that similar observations on the selection of


Dow

nloa

ded

by:

UB

der

LM

U M

ünch

en

129.

187.

254.

47 -

7/2

9/20

13 1

2:50

:48

PM

low-energy conformers have been made for several crystal-lized lectin/ligand complexes [Sharon, 1993; Cambillau,1995; Rini, 1995; Weis and Drickamer, 1996; Elgavish andShaanan, 1997; Gabius, 1997a, 1998]. However, a bindingpocket of a sugar receptor can also be capable of imposingan induced fit on the ligand, documented for the antigenicdeterminant of a Salmonella lipopolysaccharide and theglcNAc-β1, 2-man torsion angle in a concanavalin A-bind-ing pentasaccharide [Bundle, 1997; Moothoo and Naismith,1998]. The acquired knowledge about the topological de-tails of the ligand is not only of purely academic interest,satisfying scientific curiosity. Aiming at medical progress,custom-made tailoring of ligand features with respect to thereceptor is guided by this information. When musing onhow to achieve advances in the design of ligand analogs,the topological information gained by NMR experiments isconducive. In addition to blocking antibodies or lectins op-timized ligands as oligosaccharides or glycomimetics mayeventually find applications as clinically beneficial thera-

peutics in antiadhesion therapy to fight viral or bacterial in-fections, undesired inflammation or tumor spread, as illus-trated in figure 11, or as targeting device in organ/celltype-selective drug delivery [Gabius, 1988, 1997b, 1998;Karlsson, 1991; Colman, 1994; Grootenhuis et al., 1994;Gabius et al., 1995, 1996; Simon, 1996; Zopf and Roth,1996; Cornejo et al., 1997; Lowe and Ward, 1997; Mahaland Bertozzi, 1997; Rice, 1997; Witczak, 1997].

Automatically, this clinical perspective prompts the ques-tion of how to achieve an optimal rational drug design. Li-gand and receptor properties will have to be exploited on theway towards this aim. Besides the description of the boundconformation the topology of the binding site can be mappedwith chemically engineered ligand analogs, as carried out forthe mistletoe lectin and galectins [Lee et al., 1992; Solís etal., 1994, 1996; Diaz-Mauriño and Solís, 1997]. If crystals ofany member of a protein family have already been analyzed,salutary information can be gleaned from their diffractionpattern for knowledge-based homology modeling.


Fig. 8. Derivation of an example for a probable lectin-bound conformation of the disaccharide gal-β1,2-gal in thecomplex with the galactose-specific mistletoe lectin (b) by plotting distance constraints of the two interresidual trNOEcontacts into the 2D representation of the energetic levels of φ, ψ-angle combinations (a). The area of overlap of the twocontour line sets obtained from the two indicated through-space contacts (see arrows, b) defines the conformationalspace which is accessible to the bound ligand. A resulting conformation is drawn and its position in the plot is marked.

a b

Dow

nloa

ded

by:

UB

der

LM

U M

ünch

en

129.

187.

254.

47 -

7/2

9/20

13 1

2:50

:48

PM


Fig. 9. Derivation of an example for a probable lectin-bound conformation of the same disaccharide, as given infigure 8, in the complex with the avian galectin from chicken liver (CG-16). The measured distance constraints point toa position of the bound ligand in the energy map (a) which is different from that one, shown in figure 8 for the case ofthe mistletoe lectin. Consequently, the galectin selects a different conformer from the central low-energy valley forbinding (b).

Fig. 10. Relevant part of a 2D ROESY spectrum of free gal′-β1,2-galβ1-R in solution with cross-peaks indica-tive of three interresidual contacts. They are reconcilable with the two independent conformations, shown in figures 8and 9.

a b

Dow

nloa

ded

by:

UB

der

LM

U M

ünch

en

129.

187.

254.

47 -

7/2

9/20

13 1

2:50

:48

PM

Knowledge-Based Homology Modeling:The Harmonious Marriage betweenTheoretical Concepts and Experimental Input

The exploitation of knowledge about the binding site ar-chitecture and the structure of the bound ligand has alreadymatured to clinical trials in several instances [Colman,1994; von Itzstein and Colman, 1996; Jackson, 1997; Hub-bard, 1997; Marrone et al., 1997; Gabius, 1998]. Havingthus explored and appreciated the potential for clinicalbenefit of this combined approach, which is guided by thecomplementarity of the techniques of crystallography andNMR with their inherently strong and weak aspects [Wag-ner et al., 1992; MacArthur et al., 1994], it is desirable toextend the range of target molecules by computational tech-niques. It is not preposterous to refer to the contributions ofcomputations as an ongoing revolution in the field of drugdesign, meeting the challenge for developing new and ef-fective lead structures [Marrone et al., 1997]. As outlined infigure 12 for a bovine galectin, the crystal structure of onemember of the family provides the essential insight into theprotein’s folding pattern and the intimate interactions be-tween lectin and ligand [Bourne et al., 1994]. This data setis the input for homology computations for other relatedproteins, e.g. a human galectin, shown in figure 12, orchicken galectins [Solís et al., 1996; Siebert et al., 1997a].This approach has similarly been employed to generate aview of the architecture of the complex between selectinsand their ligands [Weis and Drickamer, 1996; von der

Lieth, 1997]. Surely, it harbors general applicability [John-son et al., 1994; Sowdhamini et al., 1994].

To refine the accuracy of modeling, further experimentalinput on conformational features of the modeled proteinin solution is definitely welcome. Sensitive spectroscopicmethods focusing on distinct structural aspects are helpfulcandidates to supplement the computational data material.Measuring the surface accessibility of tyrosine, tryptophan,and histidine residues by interaction with a laser-excitabledye, the laser photochemically induced dynamic nuclearpolarization (CIDNP) technique has been applied to variousplant and animal lectins [Siebert et al., 1997a, c]. Unless the


Fig. 11. Therapeutic strategies to inter-fere with lectin-mediated cell adhesion byapplication of blocking reagents, i.e. lectin-specific antibodies, a ligand-occupying solu-ble lectin and an excess of tailor-made oligo-saccharides or glycomimetics which saturateligand-binding sites.

Fig. 12. Representations of the secondary structure of the proto-type galectin-1 from bovine heart with the carbohydrate-binding sites,indicated by ligand occupation, at opposing ends of the noncovalentlylinked homodimer which displays a jelly-roll motif (top) and of the ar-chitecture of one binding site, revealing an intricate network of hydro-gen bonds between ligand and receptor donor-acceptor pairs [fromBourne et al., 1994; middle part, left]. Homology-based modelingwith human galectin-1, introducing its known substitutions relative tobovine galectin, results in an illustration of the binding site based onthe computer calculations and the X-ray data for the bovine protein(middle part, right). Homology-based modeling using the structuralparameters obtained by X-ray crystallographic analysis of bovinegalectin-1 and the experimental input by the laser photo CIDNP tech-nique leads to structural depictions of one subunit of human galectin-1 (right) and an avian galectin (CG-16, see fig.¤9) with the center ofgravity of the ligand depicted as dot (bottom).

Dow

nloa

ded

by:

UB

der

LM

U M

ünch

en

129.

187.

254.

47 -

7/2

9/20

13 1

2:50

:48

PM


12

Dow

nloa

ded

by:

UB

der

LM

U M

ünch

en

129.

187.

254.

47 -

7/2

9/20

13 1

2:50

:48

PM

spectra are too difficult to be interpreted unambiguouslyowing to massive signal overlapping, this method is suit-able to control and refine the reliability of modeling withrespect to the determined parameters. When the laser-ex-citable dye is replaced by a fluorophore, the transfer of flu-orescence energy can be quantified in solution. In analogyto transfer of magnetization the actual distance betweensender and receiver is manifested in signal intensity [Lee,1997]. Unlike the measurement of NOE, which is restrictedto short distances due to the r¤–6 dependence of the dipolarinteraction, fluorescence energy transfer is a ‘molecularruler’ in the distance range of 5–100 Å [Stryer, 1978].Further evidence for side chain positioning on the surfaceor in the binding site can be gathered by chemical meth-ods such as modification by target-selective reagents or(photo-)cross-linking to group-specific probes. Elaborationof the algorithms in modeling of proteins prior to and afterdocking of the ligand will continuously be improved by theinput of empirical information.

Conclusion

When the problems of identifying and localizing a cer-tain receptor activity in a cell and of monitoring its spatialand temporal expression pattern are to be solved, a ligand isa prime candidate as tool. Only immobilization to a histo-chemically inert carrier backbone is required to yield a his-tochemical marker. Unless the receptor’s activity is blockedor impaired by tissue processing and the ligand’s interactionpotential is diminished by derivation, such ‘neoligando-

conjugates’ can find a broad range of applications [Gabiusand Bardosi, 1991; Kayser et al., 1991; Danguy et al., 1995;Kayser and Gabius, 1997]. Focusing on glycobiology, thefeasibility of chemical design of neoglycoconjugates has al-ready engendered considerable efforts [Lee and Lee, 1994].They have enabled to accrue complementary information toconventional lectin histochemistry by the exploitation ofneoglycoconjugates, termed ‘reverse lectin histochemistry’[Gabius et al., 1993; Danguy et al., 1994, 1995]. In view ofthe ample documentation of lectin expression in animal tis-sues, to which this technique contributes remarkably, it isno longer appropriate to consider the area of lectinology asa bashful search for any tenuous thread of evidence for aphysiological relevance. On the contrary, the concept of thesugar code is well established and the emphasis of researchhas shifted from detection to delineation of structural andfunctional details of lectin-carbohydrate interactions andtheir elicited signaling processes [Mandal and Brewer,1993; Gabius, 1997a, b; Villalobo and Gabius, 1998]. Suchinvestigations have uncovered a veritable degree of con-formational flexibility of ligands and are currently unravel-ing intimate details about their molecular rendez-vous witha lectin. Combinations of NMR spectroscopy and X-raycrystallography with sophisticated computer calculationsencompassing molecular mechanics, molecular dynamics,homology modeling and docking algorithms are pertinentto comprehend how the sugar language is decoded. Movingforward from this firm foundation, it is reasonable to expectproper guidance from this panel of methods on the way toan optimized rational marker or drug design with clinicalimplications.


André, S., C. Unverzagt, S. Kojima, X. Dong, C.Fink, K. Kayser, H.-J. Gabius (1997) Neo-glycoproteins with the synthetic complex bi-antennary nonasaccharide or its α2,3-/α2,6-sialylated derivatives: Their preparation, theassessment of their ligand properties for puri-fied lectins, for tumor cells in vitro and in tissuesections and their biodistribution in tumor-bearing mice. Bioconjug Chem 8: 845–855.

Arepalli, S.R., C.P.J. Glaudemans, G.D. Daves, P.Kovac, A. Bax (1995) Identification of protein-mediated indirect NOE effects in a disaccha-ride-Fab’ complex by transferred ROESY. JMagn Reson B 106: 195–198.

Asensio, J.L., F.J. Cañada, M. Bruix, A. Rodri-guez-Romero, J. Jimenez-Barbero (1995) Theinteraction of hevein with N-acetylglucos-amine-containing oligosaccharides. Solutionstructure of hevein complexed with chitobiose.Eur J Biochem 230: 621–633.

Ashwell, G., J. Harford (1982) Carbohydrate-spe-cific receptors of the liver. Annu Rev Biochem51: 531–554.

Barondes, S.H. (1984) Soluble lectins: A newclass of extracellular proteins. Science 223:1259–1264.

Bourillon, R., M. Aubery (1989) Cell surface gly-coproteins in embryonic development. Int RevCytol 116: 257–338.

Bourne, Y., B. Bolgiano, D. Liao, G. Strecker,P. Contau, O. Herzberg, T. Feizi, C. Cambil-lau (1994) Crosslinking of mammalian lectin,galectin-1, by complex biantennary saccha-rides. Nat Struct Biol 1: 863–870.

Bovin, N.V., H.-J. Gabius (1995) Polymer-immo-bilized carbohydrate ligands: Versatile chemi-cal tools for biochemistry and medical sci-ences. Chem Soc Rev 24: 413–421.

Brinck, U., M. Korabiowska, R. Bosbach, H.-J.Gabius (1998) Detection of inflammation-and neoplasia-associated alterations in humanlarge intestine by plant/invertebrate lectins,galectin-1 and neoglycoproteins. Acta Anat161: 219–233.

References

Dow

nloa

ded

by:

UB

der

LM

U M

ünch

en

129.

187.

254.

47 -

7/2

9/20

13 1

2:50

:48

PM

Brockhausen, I., H. Schachter (1997) Glycosyl-transferases involved in N- and O-glycanbiosynthesis; in Gabius H-J, S Gabius (eds):Glycosciences: Status and Perspectives. Lon-don, Chapman & Hall, pp 79–113.

Brockhausen, I., J. Schutzbach, W. Kuhns (1998)Glycoproteins and their relationship to humandisease. Acta Anat 161: 36–78.

Bundle, D.R. (1997) Antibody-oligosaccharide in-teractions determined by crystallography; inGabius H-J, S Gabius (eds): Glycosciences:Status and Perspectives. London, Chapman &Hall, pp 311–331.

Cambillau, C. (1995) 3D structure. 1. The struc-tural features of protein-carbohydrate inter-actions revealed by X-ray crystallography; inMontreuil J, JFG Vliegenthart, H Schachter(eds): Glycoproteins. Amsterdam, Elsevier,pp 29–65.

Carver, J.P. (1991) Experimental structure determi-nation of oligosaccharides. Curr Opin StructBiol 1: 716–720.

Carver, J.P. (1993) Oligosaccharides: How canflexible molecules act as signals? Pure ApplChem 65: 763–770.

Colman, P.M. (1994) Structure-based drug design.Curr Opin Struct Biol 4: 868–874.

Cook, G.M.W. (1986) Cell surface carbohydrates:Molecules in search of a function? J Cell SciSuppl 4: 45–70.

Cook, G.M.W. (1995) Glycobiology of the cell sur-face: The emergence of sugars as an importantfeature of the cell periphery. Glycobiology 5:449–461.

Cornejo, C.J., R.K. Winn, J.M. Harlan (1997) Anti-adhesion therapy. Adv Pharmacol 39: 99–142.

Cummings, R.D. (1997) Lectins as tools for glyco-conjugate purification and characterization; inGabius H-J, S Gabius (eds): Glycosciences:Status and Perspectives. London, Chapman &Hall, pp 191–199.

Danguy, A. (1995) Perspectives in modern glyco-histochemistry. Eur J Histochem 39: 5–14.

Danguy, A., F. Akif, B. Pajak, H.-J. Gabius (1994)Contribution of carbohydrate histochemis-try to glycobiology. Histol Histopathol 9:155–171.

Danguy, A., C. Decaestecker, F. Genten, I. Salmon,R. Kiss (1998) Application of lectins and neo-glycoconjugates in histology and pathology.Acta Anat 161: 206–218.

Danguy, A., K. Kayser, N.V. Bovin, H.-J. Gabius(1995) The relevance of neoglycoconjugatesfor histology and pathology. Trends GlycosciGlycotechnol 7: 261–275.

Diaz-Mauriño, T., D. Solís (1997) Analysis of pro-tein-carbohydrate interaction using engineeredligands; in Gabius H-J, S Gabius (eds): Glyco-sciences: Status and Perspectives. London,Chapman & Hall, pp 345–354.

Elgavish, S., B. Shaanan (1997) Lectin-carbo-hydrate interactions: Different folds, commonrecognition principles. Trends Biochem Sci22: 462–467.

Etzler, M.E. (1985) Plant lectins: Molecular andbiological aspects. Annu Rev Plant Physiol 36:209–234.

Feizi, T., R.A. Childs (1987) Carbohydrates asantigenic determinants of glycoproteins. Bio-chem J 245: 1–11.

Gabius, H.-J. (1987) Vertebrate lectins and theirpossible roles in fertilization, development andtumor biology. In Vivo 1: 75–84.

Gabius, H.-J. (1988) Tumor lectinology: At theintersection of carbohydrate chemistry, bio-chemistry, cell biology and oncology. AngewChem Int Ed 27: 1267–1276.

Gabius, H.-J. (1991) Detection and functions ofmammalian lectins – With emphasis on mem-brane lectins. Biochim Biophys Acta 1071:1–18.

Gabius, H.-J. (1994) Non-carbohydrate bindingpartners/domains of animal lectins. Int J Bio-chem 26: 469–477.

Gabius, H.-J. (1997a) Animal lectins. Eur JBiochem 243: 543–576.

Gabius, H.-J. (1997b) Concepts of tumor lectinol-ogy. Cancer Invest 15: 454–464.

Gabius, H.-J. (1998) The how and why of protein-carbohydrate interaction: A primer to the theo-retical concept and a guide to application indrug design. Pharm Res 15: 23–30.

Gabius, H.-J., A. Bardosi (1991) Neoglycoproteinsas tools in glycohistochemistry. Prog Histo-chem Cytochem 22/3: 1–66.

Gabius, H.-J., S. Gabius (eds) (1993) Lectins andGlycobiology. Berlin, Springer.

Gabius, H.-J., S. Gabius, T.V. Zemlyanukhina,N.V. Bovin, U. Brinck, A. Danguy, S.S. Joshi,K. Kayser, J. Schottelius, F. Sinowatz, L.F.Tietze, F. Vidal-Vanaclocha, J.-P. Zanetta(1993) Reverse lectin histochemistry: Designand application of glycoligands for detection ofcell and tissue lectins. Histol Histopathol 8:369–383.

Gabius, H.-J., K. Kayser, S. Gabius (1995) Protein-Zucker-Erkennung. Grundlagen und medizini-sche Anwendung am Beispiel der Tumorlekti-nologie. Naturwissenschaften 82: 533–543.

Gabius, S., K. Kayser, N.V. Bovin, N. Yamazaki,S. Kojima, H. Kaltner, H.-J. Gabius (1996)Endogenous lectins and neoglycoconjugates:A sweet approach to tumor diagnosis andtargeted drug delivery. Eur J Pharm Biopharm42: 250–261.

Gahmberg, C.G., M. Tolvanen (1996) Why mam-malian cell surface proteins are glycoproteins.Trends Biochem Sci 21: 308–311.

Galanina, O.E., H. Kaltner, L.S. Khraltsova, N.V.Bovin, H.-J. Gabius (1997) Further refinementof the description of the ligand-binding charac-teristics for the galactoside-binding mistletoelectin, a plant agglutinin with immunomodula-tory potency. J Mol Recognit 10: 139–147.

Geyer, H., R. Geyer (1998) Strategies for glyco-conjugate analysis. Acta Anat 161: 18–35.

Gilleron, M., H.-C. Siebert, H. Kaltner, C.-W.von der Lieth, T. Kozár, K.M. Halkes, E.Y.Korchagina, N.V. Bovin, H.-J. Gabius, J.F.G.Vliegenthart (1998) Conformer selection anddifferential restriction of ligand mobility bya plant lectin. Conformational behavior ofGalβ1-3GlcNAcβ1-R, Galβ1-3GalNAcβ1-Rand Galβ1-2Galβ1-R′ in the free state andcomplexed with mistletoe lectin as revealed byrandom walk and conformational clusteringmolecular mechanics calculations, moleculardynamics simulations and nuclear Overhauserexperiments. Eur J Biochem 252: 416–427.

Grootenhuis, P.D.J., C.A.A. van Boeckel, C.A.G.Haasnoot (1994) Carbohydrates and drug dis-covery – The role of computer simulation.Trends Biotechnol 12: 9–14.

Hakomori, S. (1989) Aberrant glycosylation in tu-mors and tumor-associated carbohydrate anti-gens. Adv Cancer Res 52: 257–331.

Hakomori, S. (1998) Cancer-associated glyco-sphingolipid antigens: Their structure, organi-zation and function. Acta Anat 161: 79–90.

Hardy, B.J. (1997) The glycosidic linkage flexibil-ity and time-scale similarity hypotheses. J MolStruct 395/396: 187–200.

Homans, S.W. (1995) 3D structure. 2. Three-dimensional structures of oligosaccharidesexplored by NMR and computer calculations;in Montreuil J, JFG Vliegenthart, H Schach-ter (eds): Glycoproteins. Amsterdam, Elsevier,pp 67–86.

Hooper, L.V., S.M. Manzella, J.U. Baenziger(1997) The biology of sulfated oligosaccha-rides; in Gabius H-J, S Gabius (eds): Glyco-sciences: Status and Perspectives. London,Chapman & Hall, pp 261–276.

Hounsell, E.F. (1997) Methods of glycoconjugateanalysis; in Gabius H-J, S Gabius (eds): Glyco-sciences: Status and Perspectives. London,Chapman & Hall, pp 15–29.

Hubbard, R.E. (1997) Can drugs be designed? CurrOpin Biotechnol 8: 696–700.

Hull, W.E. (1994) Experimental aspects of two-dimensional NMR; in Croasmun WR, RMKCarlson (eds): Two-Dimensional NMR-Spec-troscopy: Applications for Chemists andBiochemists. New York, VCH Publishers,pp 67–456.

Imberty, A. (1997) Oligosaccharide structures:Theories versus experiment. Curr Opin StructBiol 7: 617–623.

Imberty, A., E. Mikros, J. Koca, R. Mollicone, R.Oriol, S. Pérez (1995) Computer simulationof histo-blood group oligosaccharides: Energymaps of all constituting disaccharides andpotential energy surfaces of 14 ABH andLewis carbohydrate antigens. Glycoconj J 12:331–349.

Jackson, R.C. (1997) Contributions of proteinstructure-based drug design to cancer chemo-therapy. Semin Oncol 24: 164–172.

Jardetzky, O. (1980) On the nature of molecularconformations inferred from high-resolutionNMR. Biochim Biophys Acta 621: 227–232.

Johnson, M.S., N. Srinivasan, R. Sowdhamini, T.L.Blundell (1994) Knowledge-based protein-modeling. Crit Rev Biochem Mol Biol 29:1–68.


Dow

nloa

ded

by:

UB

der

LM

U M

ünch

en

129.

187.

254.

47 -

7/2

9/20

13 1

2:50

:48

PM

Kaltner, H., B. Stierstorfer (1998) Animal lectinsas cell adhesion molecules. Acta Anat 161:162–179.

Kannan, S., M.K. Nair (1997) Lectins and neo-glycoproteins in histopathology; in GabiusH-J, S Gabius (eds): Glycosciences: Statusand Perspectives. London, Chapman & Hall,pp 563–583.

Karlsson, K.-A. (1991) Glycobiology: A growingfield for drug design. Trends Pharmacol Sci 12:265–272.

Kayser, K., H.-J. Gabius (1997) Graph theoryand the entropy concept in histochemistry.Theoretical considerations, application in his-topathology and the combination with recep-tor-specific approaches. Prog Histochem Cy-tochem 32/2: 1–106.

Kayser, K., H.-J. Gabius, S. Gabius (1991) Bi-otinylated ligands as markers for receptor-binding sites. An alternative for immunohisto-chemistry. Zentralbl Pathol 137: 473–478.

Kocourek, J. (1986) Historical background; inLiener IE, N Sharon, IJ Goldstein (eds): TheLectins: Properties, Functions and Applica-tions in Biology and Medicine. New York,Academic Press, pp 1–32.

Kopitz, J. (1997) Glycolipids: Structure and func-tion; in Gabius H-J, S Gabius (eds): Glyco-sciences: Status and Perspectives. London,Chapman & Hall, pp 163–189.

Kozár, T., C.-W. von der Lieth (1997) Efficientmodeling protocols for oligosaccharides: Fromvacuum to solvent. Glycoconj J 14: 925–933.

Kozár, T., F. Petrak, Z. Galova, I. Tvaroska (1990)RAMM – A new procedure for theoretical con-formational analysis of carbohydrates. Carbo-hydr Res 204: 27–36.

Kresse, H. (1997) Proteoglycans: Structure andfunctions; in Gabius H-J, S Gabius (eds): Gly-cosciences: Status and Perspectives. London,Chapman & Hall, pp 201–222.

Laine, R.A. (1997) The information-storing poten-tial of the sugar code; in Gabius H-J, S Gabius(eds): Glycosciences: Status and Perspectives.London, Chapman & Hall, pp 1–14.

Lee, R.T., H.-J. Gabius, Y.C. Lee (1992) Ligand-binding characteristics of the major mistletoelectin. J Biol Chem 267: 23722–23727.

Lee, R.T., H.-J. Gabius, Y.C. Lee (1994) The sugar-combining area of galactose-specific toxiclectin of mistletoe extends beyond the termi-nal sugar residue: Comparison with a homolo-gous toxic lectin, ricin. Carbohydr Res 254:269–276.

Lee, Y.C. (1997) Fluorescence spectrometry instudies of carbohydrate-protein interactions.J Biochem 121: 818–825.

Lee, Y.C., R.T. Lee (eds) (1994) Neoglycoconju-gates. Preparation and Applications. SanDiego, Academic Press.

Lian, L.Y., I.L. Barsukov, M.J. Sutcliffe, K.H. Sze,G.C.K. Roberts (1994) Protein-ligand interac-tions: Exchange processes and determinationof ligand conformation and protein-ligand con-tacts. Methods Enzymol 239: 657–700.

Lotan, R., G.L. Nicolson (1979) Purification ofcell membrane glycoproteins by lectin affinitychromatography. Biochim Biophys Acta 559:329–376.

Lowe, J.B., P.A. Ward (1997) Therapeutic inhibi-tion of carbohydrate-protein interactions invivo. J Clin Invest 99: 822–826.

MacArthur, M.W., P.C. Driscoll, J.M. Thornton(1994) NMR and crystallography: Comple-mentary approaches to structure determina-tion. Trends Biotechnol 12: 149–153.

Mahal, L.K., C.R. Bertozzi (1997) Engineered cellsurfaces: Fertile ground for molecular land-scaping. Chem Biol 4: 415–422.

Mandal, D.K., C.F. Brewer (1993) Lectin-gly-coconjugate cross-linking interactions; inGabius H-J, S Gabius (eds): Lectins and Gly-cobiology. Berlin, Springer, pp 117–128.

Mann, P.L. (1988) Membrane oligosaccharides:Structure and function during differentiation.Int Rev Cytol 112: 67–96.

Mann, P.L., R.E. Waterman (1998) Glycocoding asan information management system in embry-onic development. Acta Anat 161: 153–161.

Marrone, T.J., J.M. Briggs, J.A. McCammon(1997) Structure-based drug design: Computa-tional advances. Annu Rev Pharmacol Toxicol37: 71–90.

Montreuil, J. (1995) The history of glycoproteinresearch, a personal view; in Montreuil J, JFGVliegenthart, H Schachter (eds): Glycopro-teins. Amsterdam, Elsevier, pp 1–12.

Moothoo, D.N., J.H. Naismith (1998) Con-canavalin A distorts the β-GlcNAc-1,2-Manlinkage of GlcNAc-1,2-α-1,3-[βGlcNAc-1,2-α-Man-1,6]-Man upon binding. Glycobiology8: 173–181.

Ni, F. (1994) Recent developments in transferredNOE methods. Prog Nucleic Magn ResonSpectrosc 26: 517–606.

Pavelka, M. (1997) Topology of glycosylation – Ahistochemist’s view; in Gabius H-J, S Gabius(eds): Glycosciences: Status and Perspectives.London, Chapman & Hall, pp 115–120.

Pearlman, D.A. (1994) How is an NMR structurebest defined? An analysis of molecular dynam-ics distance-based approaches. J Biomol NMR4: 1–16.

Pérez, S., A. Imberty, J.P. Carver (1994) Molecu-lar modeling: An essential component in thestructure determination of oligosaccharidesand polysaccharides. Adv Comput Biol 1:147–202.

Peters, T., B.M. Pinto (1996) Structure and dynam-ics of oligosaccharides: NMR and modelingstudies. Curr Opin Struct Biol 6: 710–720.

Peumans, W.J., E.J.M. van Damme (1995) The roleof lectins in plant defence. Histochem J 27:253–271.

Poppe, L., C.-W. von der Lieth, J. Dabrowski(1990) Conformation of the glycolipid globo-side head group in various solvents and inthe micelle-bound state. J Am Chem Soc 112:7762–7771.

Poppe, L., G.S. Brown, J.S. Philo, P.V. Nikrad,B.H. Shah (1997) Conformation of sLex

tetrasaccharide, free in solution and bound toE-, P-, and L-selectin. J Am Chem Soc 119:1727–1736.

Rasmussen, K. (1997) How to develop force fields:An account of the emergence of potential en-ergy functions for saccharides. J Mol Struct395/396: 91–106.

Rhodes, J.M., J.D. Milton (eds) (1998) LectinMethods and Protocols. Totowa, HumanaPress.

Rice, K.G. (1997) Glycoconjugate-mediated drugtargeting; in Gabius H-J, S Gabius (eds): Gly-cosciences: Status and Perspectives. London,Chapman & Hall, pp 471–483.

Rini, J.M. (1995) Lectin structure. Annu Rev Bio-phys Biomol Struct 24: 551–577.

Rüdiger, H. (1997) Structure and function of plantlectins; in Gabius H-J, S Gabius (eds): Glyco-sciences: Status and Perspectives. London,Chapman & Hall, pp 415–438.

Rüdiger, H. (1998) Plant lectins – More than justtools for glycoscientists. Occurrence, structureand possible functions of plant lectins. ActaAnat 161: 130–152.

Schmidt, R.R. (1997) Strategies for chemicalsynthesis of carbohydrate structures; in GabiusH-J, S Gabius (eds): Glycosciences: Statusand Perspectives. London, Chapman & Hall,pp 31–53.

Sharon, N. (1993) Lectin-carbohydrate complexesof plants and animals: An atomic view. TrendsBiochem Sci 18: 221–226.

Sharon, N. (1998) Glycoproteins now and then.Acta Anat 161: 7–17.

Sharon, N., H. Lis (1987) A century of lectin re-search (1888–1988). Trends Biochem Sci 12:488–491.

Sharon, N., H. Lis (1989) Lectins as cell recogni-tion molecules. Science 246: 227–234.

Sharon, N., H. Lis (1997) Glycoproteins: Structureand function; in Gabius H-J, S Gabius (eds):Glycosciences: Status and Perspectives. Lon-don, Chapman & Hall, pp 133–162.

Siebert, H.-C., R. Adar, R. Arango, M. Burchert,H. Kaltner, G. Kayser, E. Tajkhorshid, C.-W.von der Lieth, R. Kaptein, N. Sharon, J.F.G.Vliegenthart, H.-J. Gabius (1997a) Involve-ment of laser photo CIDNP (chemically in-duced dynamic nuclear polarization)-reactiveamino acid side chains in ligand binding bygalactoside-specific lectins in solution. Simi-larities in the role of tryptophan/tyrosine res-idues for ligand binding between a plant agglu-tinin and mammalian/avian galectins and thedetection of an influence of single-site mutage-nesis on surface presentation of spatially sepa-rated residues. Eur J Biochem 249: 27–38.

Siebert, H.-C., M. Gilleron, H. Kaltner, C.-W. vonder Lieth, T. Kozár, N.V. Bovin, E.Y. Korcha-gina, J.F.G. Vliegenthart, H.-J. Gabius (1996)NMR-based, molecular dynamics- and randomwalk molecular mechanics-supported studyof conformational aspects of a carbohydrateligand Galβ1-2Galβ1-R for an animal galectinin the free and in the bound state. BiochemBiophys Res Commun 219: 205–212.

Siebert, H.-C., C.-W. von der Lieth, M. Gilleron,G. Reuter, J. Wittmann, J.F.G. Vliegenthart,H.-J. Gabius (1997b) Carbohydrate-protein in-teraction; in Gabius H-J, S Gabius (eds): Gly-cosciences: Status and Perspectives. London,Chapman & Hall, pp 291–310.


Dow

nloa

ded

by:

UB

der

LM

U M

ünch

en

129.

187.

254.

47 -

7/2

9/20

13 1

2:50

:48

PM

Siebert, H.-C., C.-W. von der Lieth, R. Kaptein, J.J.Beintema, K. Dijkstra, N. van Nuland, U.M.S.Soedjanaatmadja, A. Rice, J.F.G. Vliegenthart,C.S. Wright, H.-J. Gabius (1997c) Role of aro-matic amino acids in carbohydrate binding ofplant lectins. Laser photo CIDNP (chemicallyinduced dynamic nuclear polarization) study ofhevein domain-containing lectins. Proteins 28:268–284.

Simon, P.M. (1996) Pharmaceutical oligosaccha-rides. Drug Discov Today 1: 522–528.

Solís, D., J. Jimenez-Barbero, M. Martin-Lomas,T. Diaz-Mauriño (1994) Probing hydrogen-bonding interactions of bovine heart galectin-1and methyl β-lactoside by use of engineeredligands. Eur J Biochem 223: 107–114.

Solís, D., A. Romero, H. Kaltner, H.-J. Gabius, T.Diaz-Mauriño (1996) Different architecture ofthe combining sites of two chicken galectinsrevealed by chemical-mapping studies withsynthetic ligand derivatives. J Biol Chem 271:12744–12748.

Sowdhamini, R., S.D. Ruffino, T.L. Blundell(1994) The construction and use of databasesof protein domain topologies and templates.Chemtracts 5: 291–306.

Spicer, S.S., B.A. Schulte (1992) Diversity of cellglycoconjugates shown histochemically: Aperspective. J Histochem Cytochem 40: 1–38.

Stowell, C.P., Y.C. Lee (1980) Neoglycoproteins:The preparation and application of syntheticglycoproteins. Adv Carbohydr Chem Biochem37: 225–281.

Stryer, L. (1978) Fluorescence energy transfer asa spectroscopic ruler. Annu Rev Biochem 47:819–846.

Varki, A. (1996) ‘Unusual’ modifications and va-riations of vertebrate oligosaccharides: Are wemissing the flowers for the trees? Glycobiology6: 707–710.

Varki, A. (1998) Factors controlling the glycosyla-tion potential of the Golgi apparatus. TrendsCell Biol 8: 34–40.

Varki, A., J. Marth (1995) Oligosaccharides invertebrate development. Semin Dev Biol 6:127–138.

Vasta, G.R. (1992) Invertebrate lectins: Distri-bution, synthesis, molecular biology andfunction; in Allen HJ, EC Kisailus (eds):Glycoconjugates: Composition, Structure andFunction. New York, Dekker, pp 543–634.

Villalobo, A., H.-J. Gabius (1998) Signaling path-ways for transduction of the initial message ofthe glycocode into cellular responses. ActaAnat 161: 110–129.

von der Lieth, C.-W. (1997) The role of Ca2+ in thebinding of carbohydrates to C-type lectinsas revealed by molecular mechanics andmolecular dynamics calculations; in Banci L,P Comba (eds): Molecular Modeling andDynamics of Bioinorganic Systems. Dor-drecht, Kluwer, pp 167–190.

von der Lieth, C.-W., E. Lang, T. Kozár (1997a)Carbohydrates: Second-class citizens in bio-medicine and in bioinformatics?; in HofestädtR, T Lengauer, M Löffler, D Schomburg (eds):Bioinformatics. Berlin, Springer, pp 147–155.

von der Lieth, C.-W., T. Kozár, W.E. Hull (1997b)A (critical) survey of modeling protocols usedto explore the conformational space of oligo-saccharides. J Mol Struct 395/396: 225–244.

von Itzstein, M., P.M. Colman (1996) Design andsynthesis of carbohydrate-based inhibitors ofcarbohydrate-protein interaction. Curr OpinStruct Biol 6: 703–709.

Wagner, G., S.G. Hyberts, T.F. Havel (1992) NMRstructure determination in solution: A cri-tique and comparison with X-ray crystallogra-phy. Annu Rev Biophys Biomol Struct 21:167–198.

Weis, W.I., K. Drickamer (1996) Structural basisof lectin-carbohydrate recognition. Annu RevBiochem 65: 441–473.

Witczak, Z.J. (1997) Carbohydrates as new and oldtargets for future drug design; in Witczak ZJ,KA Nieforth (eds): Carbohydrates in DrugDesign. New York, Dekker, pp 1–37.

Woods, R.J. (1996) The application of molecu-lar modeling techniques to the determinationof oligosaccharide solution conformations; inLipkowitz K, DB Boyd (eds): Reviews inComputational Chemistry, New York, VCHPublishers, vol 9, pp 129–165.

Woods, R.J., R.A. Dwek, C.J. Edge, B. Fraser-Reid(1995) Molecular mechanical and molecu-lar dynamical simulations of glycoproteinsand oligosaccharides. J Phys Chem 99:3832–3846.

Zanetta, J.-P. (1997) Lectins and carbohydrates inanimal cell adhesion and control of cell prolif-eration; in Gabius H-J, S Gabius (eds): Glyco-sciences: Status and Perspectives. London,Chapman & Hall, pp 439–458.

Zanetta, J.-P. (1998) Structure and functions oflectins in the central and peripheral nervoussystem. Acta Anat 161: 180–195.

Zopf, D., S. Roth (1996) Oligosaccharide anti-in-fective agents. Lancet 347: 1017–1021.

Zschäbitz, A. (1998) Glycoconjugate expressionand cartilage development of the cranial skele-ton. Acta Anat 161: 254–273.


Dow

nloa

ded

by:

UB

der

LM

U M

ünch

en

129.

187.

254.

47 -

7/2

9/20

13 1

2:50

:48

PM

a Lectin Ligands: New Insights into H.-C. Siebert Their ... · mechanics, molecular dynamics and...

Documents

Transcript of a Lectin Ligands: New Insights into H.-C. Siebert Their ... · mechanics, molecular dynamics and...